https://github.com/anthonymrios/pymetamap

Python wraper for MetaMap
https://github.com/anthonymrios/pymetamap

biomedical-informatics named-entity-recognition natural-language-processing nlp python

Last synced: 3 days ago
JSON representation

Python wraper for MetaMap

• Host: GitHub
• URL: https://github.com/anthonymrios/pymetamap
• Owner: AnthonyMRios
• Created: 2015-01-19T07:26:26.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2020-07-22T19:58:16.000Z (over 4 years ago)
• Last Synced: 2024-04-26T14:45:03.759Z (9 months ago)
• Topics: biomedical-informatics, named-entity-recognition, natural-language-processing, nlp, python
• Language: Python
• Size: 45.9 KB
• Stars: 168
• Watchers: 9
• Forks: 61
• Open Issues: 12
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE-2.0.txt

Awesome Lists containing this project

README

        
pymetamap

=========

Python wrapper around `MetaMap `_.

This will take a list of sentences and extract concepts using MetaMap

then return them in the form of a list of Concept objects.

**Note:** This code does **not** work with Windows because of my use of NamedTemporaryFile in SubprocessBackend.py.

How to Install

--------------

First, install MetaMap by using the following instructions: https://metamap.nlm.nih.gov/Installation.shtml

Next, pymetamap can be installed using the following command:

>>> python setup.py install

Example Usage

-------------

To start you must create a MetaMap instance from the pymetamap package.

::

    >>> from pymetamap import MetaMap

    >>> mm = MetaMap.get_instance('/opt/public_mm/bin/metamap12')

You must supply the metamap binary to ``get_instance()`` in order to

extract concepts. Depending on where you installed MetaMap and depending on the version you are using, you will need to change the ``/opt/public_mm/bin/metamap12`` to the correct location.

For example, if you installed the 2016 version of MetaMap, then the binary will be called ``metamap16``.

We now support MetaMapLite. To use MetaMapLite, rather than MetaMap, create a MetaMapLite instance:

::

    >>> from pymetamap import MetaMapLite

    >>> mm = MetaMapLite.get_instance('/opt/public_mm_lite_3.6.2rc3/')

**Note:** The MetaMap binary path and MetaMapLite home directory should be absolute.

To extract concepts from a sentence with MetaMapLite and MetaMap use the ``extract_concepts()``

method. This method takes a list of sentences as input and will return

a list of Concept objects.

::

    >>> sents = ['Heart Attack', 'John had a huge heart attack']

    >>> concepts,error = mm.extract_concepts(sents,[1,2])

    >>> for concept in concepts:

    ...     print concept

    Concept(index='1', mm='MM', score='14.64', preferred_name='Myocardial Infarction', cui='C0027051', semtypes='[dsyn]', trigger='["Heart attack"-tx-1-"Heart Attack"]', location='TX', pos_info='1:12', tree_codes='C14.280.647.500;C14.907.585.500')

    Concept(index='2', mm='MM', score='13.22', preferred_name='Myocardial Infarction', cui='C0027051', semtypes='[dsyn]', trigger='["Heart attack"-tx-1-"heart attack"]', location='TX', pos_info='17:12', tree_codes='C14.280.647.500;C14.907.585.500')

This example shows two separate concepts extracted via MetaMap from two

different sentences (sentence 1 and sentence 2).

More Information

----------------

Licensed under `Apache 2.0 `_.

Written by Anthony Rios

Special thanks to `joaopalotti `_ and others for their contributions.